在被动传感器数据中,有明确的动态调节模式,遵循过度饮食和清洗行为
Jonathan E Butner1, Laura M Thornton2, Robyn E Kilshaw1
1Department of Psychology, University of Utah, Salt Lake City, Utah, USA.
The International journal of eating disorders
|April 11, 2025
概括
智能手表可以跟踪心率和活动变化在暴饮暴食和清洗行为在个人的饮食障碍. 这些数据显示,对监测治疗进展和减少暴饮暴食频率有希望.
科学领域:
- 精神病学和行为科学 精神病学和行为科学
- 生物医学工程 生物医学工程
- 数字健康数字健康
背景情况:
- 暴饮暴食和排泄是暴饮暴食障碍 (BED) 和神经性嗜食症 (BN) 的关键症状.
- 这些行为与严重的健康问题和痛苦有关.
- 了解生理调节动态对于有效的干预至关重要.
研究的目的:
- 为了描述心率 (HR) 和身体活动调节动力学,在过度饮食和清洗行为后.
- 为了将这些动态与控制期和彼此进行比较.
主要方法:
- 利用了BEGIN研究30天内295名参与者的数据.
- 通过恢复记录应用程序收集的过度饮食/清洗数据.
- 使用Apple Watch设备测量步骤和HR.
- 模拟人力资源的监管动态和使用多层模型的步骤.
主要成果:
- 在暴饮暴食后,HR调节动态失调,在清洗后混合,不同于同源控制时期.
- 与对照组相比,步骤调节动力学在 binges (dysregulated) 和 purges (homeostatic) 之间存在显著差异.
- 无论是HR还是步骤动态,在过度饮食和清洗行为之后都显示出不同的模式.
结论:
- 商业智能手表可以捕捉复杂的人力资源和体力活动动态后狂欢/净化.
- 这些动态显示出作为追踪BED和BN治疗进展的数字标记物的潜力.
- 智能手表数据可以帮助监测和减少饮食过度和清洗频率.
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